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Exploring Barriers to the Adoption of Internet of Things-Based Precision Agriculture Practices

Author

Listed:
  • Gaganpreet Singh Hundal

    (Sociotechnical Systems Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139, USA)

  • Chad Matthew Laux

    (Purdue Polytechnic, Purdue University, West Lafayette, IN 47905, USA)

  • Dennis Buckmaster

    (College of Agriculture, Purdue University, West Lafayette, IN 47905, USA)

  • Mathias J Sutton

    (Purdue Polytechnic, Purdue University, West Lafayette, IN 47905, USA)

  • Michael Langemeier

    (College of Agriculture, Purdue University, West Lafayette, IN 47905, USA)

Abstract

The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review describes low adoption of Internet of Things (IoT)-based precision agriculture technologies, such as variable rate fertilizer (39%), variable rate pesticide (8%), variable rate irrigation (4%), cloud-based data analytics (21%) and telematics (10%) amongst Midwestern row crop producers. Barriers to the adoption of IoT-based precision agriculture technologies cited in the literature include cost effectiveness, power requirements, wireless communication range, data latency, data scalability, data storage, data processing and data interoperability. Therefore, this study focused on exploring and understanding decision-making variables related to barriers through three focus group interview sessions conducted with eighteen ( n = 18) subject matter experts (SME) in IoT- based precision agriculture practices. Dependency relationships described between cost, data latency, data scalability, power consumption, communication range, type of wireless communication and precision agriculture application is one of the main findings. The results might inform precision agriculture practitioners, producers and other stakeholders about variables related to technical and operational barriers for the adoption of IoT-based precision agriculture practices.

Suggested Citation

  • Gaganpreet Singh Hundal & Chad Matthew Laux & Dennis Buckmaster & Mathias J Sutton & Michael Langemeier, 2023. "Exploring Barriers to the Adoption of Internet of Things-Based Precision Agriculture Practices," Agriculture, MDPI, vol. 13(1), pages 1-16, January.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:1:p:163-:d:1029933
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    References listed on IDEAS

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    1. Lewis, Alan, 2001. "A focus group study of the motivation to invest: 'ethical/green' and 'ordinary' investors compared," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 30(4), pages 331-341.
    2. Shockley, Jordan M. & Dillon, Carl R. & Stombaugh, Timothy S., 2011. "A Whole Farm Analysis of the Influence of Auto-Steer Navigation on Net Returns, Risk, and Production Practices," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(1), pages 1-19, February.
    3. Frits K. Van Evert & Daniel Gaitán-Cremaschi & Spyros Fountas & Corné Kempenaar, 2017. "Can Precision Agriculture Increase the Profitability and Sustainability of the Production of Potatoes and Olives?," Sustainability, MDPI, vol. 9(10), pages 1-24, October.
    4. Schimmelpfennig, David, 2016. "Farm Profits and Adoption of Precision Agriculture," Economic Research Report 249773, United States Department of Agriculture, Economic Research Service.
    5. Athanasios Balafoutis & Bert Beck & Spyros Fountas & Jurgen Vangeyte & Tamme Van der Wal & Iria Soto & Manuel Gómez-Barbero & Andrew Barnes & Vera Eory, 2017. "Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics," Sustainability, MDPI, vol. 9(8), pages 1-28, July.
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    Cited by:

    1. Kevan W. Lamm & Lauren Pike & Lauren Griffeth & Jiyea Park & Andrews Idun, 2023. "Critical Issues Facing the Agriculture, Forestry, and Natural Resources Industries in the State of Georgia," Agriculture, MDPI, vol. 13(6), pages 1-12, June.
    2. E. M. B. M. Karunathilake & Anh Tuan Le & Seong Heo & Yong Suk Chung & Sheikh Mansoor, 2023. "The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture," Agriculture, MDPI, vol. 13(8), pages 1-26, August.

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